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一個(gè)自然語言處理的Java開源工具包。LingPipe目前已有很豐富的功能，包括主題分類（Top Classification）、命名實(shí)體識(shí)別（Named Entity Recognition）、詞性標(biāo)注（Part-of speech Tagging）、句題檢測(cè)（Sentence Detection）、查詢拼寫檢查（Query Spell Checking）、興趣短語檢測(cè)（Interseting Phrase Detection）、聚類（Clustering）、字符語言建模（Character Language Modeling）、醫(yī)學(xué)文獻(xiàn)下載/解析/索引（MEDLINE Download, Parsing and Indexing）、數(shù)據(jù)庫文本挖掘（Database Text Mining）、中文分詞（Chinese Word Segmentation）、情感分析（Sentiment Analysis）、語言辨別（Language Identification）等API。
標(biāo)簽： LingPipe Java 自然語言處理 開源
上傳時(shí)間： 2013-12-04
上傳用戶：15071087253
3G Mobile Open Wide Door For E-commerce The 3G mobile Internet business in 3G era will obtain rapid development, but it still cannot become the ma in 3G era. In the age of 3G speech business, but is still a subject of value-added business will have great development, the 3G mobile Internet business.
標(biāo)簽： E-commerce 3G Internet business
上傳時(shí)間： 2017-03-23
上傳用戶：zjf3110
Java Media APIs: Cross-Platform Imaging, Media, and Visualization presents integrated Java media solutions that demonstrate the best practices for using this diverse collection. According to Sun MicroSystems, "This set of APIs supports the integration of audio and video clips, animated presentations, 2D fonts, graphics, and images, as well as speech input/output and 3D models." By presenting each API in the context of its appropriate use within an integrated media application, the authors both illustrate the potential of the APIs and offer the architectural guidance necessary to build compelling programs.
標(biāo)簽： Media Java Cross-Platform Visualization
上傳時(shí)間： 2013-12-04
上傳用戶：hanli8870
Face Transfer is a method for mapping videorecorded perfor-mances of one individual to facial animations of another. It extracts visemes (speech-related mouth articulations), expressions, and three-dimensional (3D) pose from monocular video or 鏗乴m footage.
標(biāo)簽： videorecorded perfor-mances individual Transfer
上傳時(shí)間： 2014-01-11
上傳用戶：2467478207
The philosophy of the book is to present various pattern recognition tasks in a unified way, including image analysis, speech processing, and communication applications. Despite their differences, these areas do share common features and their study can only benefit from a unified approach.
標(biāo)簽： recognition philosophy pattern present
上傳時(shí)間： 2017-05-05
上傳用戶：plsee
C Algorithms for Real-Time DSP Chapter 5 presents several real-time DSP applications, including speech compression music signal processing radar signal processing and adaptive signal processing techniques.
標(biāo)簽： applications Algorithms Real-Time DSP
上傳時(shí)間： 2013-12-27
上傳用戶：王者A
this file has codes that describes how to ccmpute the signal spectrum , the power spectrum, how to calculate the autocorrelation sequence of a signal, how to calculate the autoregressive coeffecients of a signal,and how to reduce the noisy elements in a speech sample.
標(biāo)簽： spectrum describes how the
上傳時(shí)間： 2017-07-23
上傳用戶：金宜
Commercially available active noise control headphones rely on fixed analog controllers to drive "anti-noise" loudspeakers. Our design uses an adaptive controller to optimally cancel unwanted acoustic noise. This headphone would be particularly useful for workers who operate or work near heavy machinery and engines because the noise is selectively eliminated. Desired sounds, such as speech and warning signals, are left to be heard clearly. The adaptive control algorithm is implemented on a Texas Instruments (TI™ ) 1 TMS320C30GEL digital signal processor (DSP), which drives a Sony CD550 headphone/microphone system. Our experiments indicate that adaptive noise control results in a dramatic improvement in performance over fixed noise control. This improvement is due to the availability of high-performance programmable DSPs and the self-optimizing and tracking capabilities of the adaptive controller in response to the surrounding noise.
標(biāo)簽： Commercially controllers headphones available
上傳時(shí)間： 2013-12-04
上傳用戶：dyctj
This report presents a tutorial of fundamental array processing and beamforming theory relevant to microphone array speech processing. A microphone array consists of multiple microphones placed at different spatial locations. Built upon a knowledge of sound propagation principles, the multiple inputs can be manipulated to enhance or attenuate signals emanating from particular directions. In this way, microphone arrays provide a means of enhancing a desired signal in the presence of corrupting noise sources. Moreover, this enhancement is based purely on knowledge of the source location, and so microphone array techniques are applicable to a wide variety of noise types. Microphone arrays have great potential in practical applications of speech processing, due to their ability to provide both noise robustness and hands-free signal acquisition.
標(biāo)簽： Microphone array Tutorial Array Signal Processing
上傳時(shí)間： 2016-06-12
上傳用戶：halias
The 4.0 kbit/s speech codec described in this paper is based on a Frequency Domain Interpolative (FDI) coding technique, which belongs to the class of prototype waveform Interpolation (PWI) coding techniques. The codec also has an integrated voice activity detector (VAD) and a noise reduction capability. The input signal is subjected to LPC analysis and the prediction residual is separated into a slowly evolving waveform (SEW) and a rapidly evolving waveform (REW) components. The SEW magnitude component is quantized using a hierarchical predictive vector quantization approach. The REW magnitude is quantized using a gain and a sub-band based shape. SEW and REW phases are derived at the decoder using a phase model, based on a transmitted measure of voice periodicity. The spectral (LSP) parameters are quantized using a combination of scalar and vector quantizers. The 4.0 kbits/s coder has an algorithmic delay of 60 ms and an estimated floating point complexity of 21.5 MIPS. The performance of this coder has been evaluated using in-house MOS tests under various conditions such as background noise. channel errors, self-tandem. and DTX mode of operation, and has been shown to be statistically equivalent to ITU-T (3.729 8 kbps codec across all conditions tested.
標(biāo)簽： frequency-domain interpolation performance Design kbit_s speech coder based and of
上傳時(shí)間： 2018-04-08
上傳用戶：kilohorse
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